{
 "cells": [
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "## Main Idea\n",
    " \n",
    "I read [all public kernels about EfficientDet in kaggle community](https://www.kaggle.com/search?q=efficientdet+in%3Anotebooks) and understand that kaggle don't have really good working public kernels with good score. Why? You can see below picture about COCO AP for different architectures, I think everyone should be able to use such a strong tools EfficientDet for own research, lets do it!\n",
    "\n",
    "<img src='https://miro.medium.com/max/2400/0*ApAKUWtseHcvRV2U.png' width=400>   \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "## Dependencies and imports\n",
    "\n",
    "In this kernel used github repos [efficientdet-pytorch](https://github.com/rwightman/efficientdet-pytorch) and [pytorch-image-models](https://github.com/rwightman/pytorch-image-models) by [@rwightman](https://www.kaggle.com/rwightman). Don't forget add stars ;)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_kg_hide-input": true,
    "_kg_hide-output": true,
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [],
   "source": [
    "!pip install --no-deps '../input/timm-package/timm-0.1.26-py3-none-any.whl' > /dev/null\n",
    "!pip install --no-deps '../input/pycocotools/pycocotools-2.0-cp37-cp37m-linux_x86_64.whl' > /dev/null"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_kg_hide-input": true,
    "_kg_hide-output": true
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.insert(0, \"../input/timm-efficientdet-pytorch\")\n",
    "sys.path.insert(0, \"../input/omegaconf\")\n",
    "\n",
    "import torch\n",
    "import os\n",
    "from datetime import datetime\n",
    "import time\n",
    "import random\n",
    "import cv2\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import albumentations as A\n",
    "import matplotlib.pyplot as plt\n",
    "from albumentations.pytorch.transforms import ToTensorV2\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from torch.utils.data import Dataset,DataLoader\n",
    "from torch.utils.data.sampler import SequentialSampler, RandomSampler\n",
    "from glob import glob\n",
    "\n",
    "SEED = 42\n",
    "\n",
    "def seed_everything(seed):\n",
    "    random.seed(seed)\n",
    "    os.environ['PYTHONHASHSEED'] = str(seed)\n",
    "    np.random.seed(seed)\n",
    "    torch.manual_seed(seed)\n",
    "    torch.cuda.manual_seed(seed)\n",
    "    torch.backends.cudnn.deterministic = True\n",
    "    torch.backends.cudnn.benchmark = True\n",
    "\n",
    "seed_everything(SEED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "marking = pd.read_csv('../input/global-wheat-detection/train.csv')\n",
    "\n",
    "bboxs = np.stack(marking['bbox'].apply(lambda x: np.fromstring(x[1:-1], sep=',')))\n",
    "for i, column in enumerate(['x', 'y', 'w', 'h']):\n",
    "    marking[column] = bboxs[:,i]\n",
    "marking.drop(columns=['bbox'], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "About data splitting you can read [here](https://www.kaggle.com/shonenkov/wbf-approach-for-ensemble):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_kg_hide-output": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/sklearn/model_selection/_split.py:667: UserWarning: The least populated class in y has only 1 members, which is less than n_splits=5.\n",
      "  % (min_groups, self.n_splits)), UserWarning)\n"
     ]
    }
   ],
   "source": [
    "skf = StratifiedKFold(n_splits=5, shuffle=True, random_state=42)\n",
    "\n",
    "df_folds = marking[['image_id']].copy()\n",
    "df_folds.loc[:, 'bbox_count'] = 1\n",
    "df_folds = df_folds.groupby('image_id').count()\n",
    "df_folds.loc[:, 'source'] = marking[['image_id', 'source']].groupby('image_id').min()['source']\n",
    "df_folds.loc[:, 'stratify_group'] = np.char.add(\n",
    "    df_folds['source'].values.astype(str),\n",
    "    df_folds['bbox_count'].apply(lambda x: f'_{x // 15}').values.astype(str)\n",
    ")\n",
    "df_folds.loc[:, 'fold'] = 0\n",
    "\n",
    "for fold_number, (train_index, val_index) in enumerate(skf.split(X=df_folds.index, y=df_folds['stratify_group'])):\n",
    "    df_folds.loc[df_folds.iloc[val_index].index, 'fold'] = fold_number"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "## Albumentations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_train_transforms():\n",
    "    return A.Compose(\n",
    "        [\n",
    "            A.RandomSizedCrop(min_max_height=(800, 800), height=1024, width=1024, p=0.5),\n",
    "            A.OneOf([\n",
    "                A.HueSaturationValue(hue_shift_limit=0.2, sat_shift_limit= 0.2, \n",
    "                                     val_shift_limit=0.2, p=0.9),\n",
    "                A.RandomBrightnessContrast(brightness_limit=0.2, \n",
    "                                           contrast_limit=0.2, p=0.9),\n",
    "            ],p=0.9),\n",
    "            A.ToGray(p=0.01),\n",
    "            A.HorizontalFlip(p=0.5),\n",
    "            A.VerticalFlip(p=0.5),\n",
    "            A.Resize(height=512, width=512, p=1),\n",
    "            A.Cutout(num_holes=8, max_h_size=64, max_w_size=64, fill_value=0, p=0.5),\n",
    "            ToTensorV2(p=1.0),\n",
    "        ], \n",
    "        p=1.0, \n",
    "        bbox_params=A.BboxParams(\n",
    "            format='pascal_voc',\n",
    "            min_area=0, \n",
    "            min_visibility=0,\n",
    "            label_fields=['labels']\n",
    "        )\n",
    "    )\n",
    "\n",
    "def get_valid_transforms():\n",
    "    return A.Compose(\n",
    "        [\n",
    "            A.Resize(height=512, width=512, p=1.0),\n",
    "            ToTensorV2(p=1.0),\n",
    "        ], \n",
    "        p=1.0, \n",
    "        bbox_params=A.BboxParams(\n",
    "            format='pascal_voc',\n",
    "            min_area=0, \n",
    "            min_visibility=0,\n",
    "            label_fields=['labels']\n",
    "        )\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "## Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "TRAIN_ROOT_PATH = '../input/global-wheat-detection/train'\n",
    "\n",
    "class DatasetRetriever(Dataset):\n",
    "\n",
    "    def __init__(self, marking, image_ids, transforms=None, test=False):\n",
    "        super().__init__()\n",
    "\n",
    "        self.image_ids = image_ids\n",
    "        self.marking = marking\n",
    "        self.transforms = transforms\n",
    "        self.test = test\n",
    "\n",
    "    def __getitem__(self, index: int):\n",
    "        image_id = self.image_ids[index]\n",
    "        \n",
    "        if self.test or random.random() > 0.5:\n",
    "            image, boxes = self.load_image_and_boxes(index)\n",
    "        else:\n",
    "            image, boxes = self.load_cutmix_image_and_boxes(index)\n",
    "\n",
    "        # there is only one class\n",
    "        labels = torch.ones((boxes.shape[0],), dtype=torch.int64)\n",
    "        \n",
    "        target = {}\n",
    "        target['boxes'] = boxes\n",
    "        target['labels'] = labels\n",
    "        target['image_id'] = torch.tensor([index])\n",
    "\n",
    "        if self.transforms:\n",
    "            for i in range(10):\n",
    "                sample = self.transforms(**{\n",
    "                    'image': image,\n",
    "                    'bboxes': target['boxes'],\n",
    "                    'labels': labels\n",
    "                })\n",
    "                if len(sample['bboxes']) > 0:\n",
    "                    image = sample['image']\n",
    "                    target['boxes'] = torch.stack(tuple(map(torch.tensor, zip(*sample['bboxes'])))).permute(1, 0)\n",
    "                    target['boxes'][:,[0,1,2,3]] = target['boxes'][:,[1,0,3,2]]  #yxyx: be warning\n",
    "                    break\n",
    "\n",
    "        return image, target, image_id\n",
    "\n",
    "    def __len__(self) -> int:\n",
    "        return self.image_ids.shape[0]\n",
    "\n",
    "    def load_image_and_boxes(self, index):\n",
    "        image_id = self.image_ids[index]\n",
    "        image = cv2.imread(f'{TRAIN_ROOT_PATH}/{image_id}.jpg', cv2.IMREAD_COLOR)\n",
    "        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB).astype(np.float32)\n",
    "        image /= 255.0\n",
    "        records = self.marking[self.marking['image_id'] == image_id]\n",
    "        boxes = records[['x', 'y', 'w', 'h']].values\n",
    "        boxes[:, 2] = boxes[:, 0] + boxes[:, 2]\n",
    "        boxes[:, 3] = boxes[:, 1] + boxes[:, 3]\n",
    "        return image, boxes\n",
    "\n",
    "    def load_cutmix_image_and_boxes(self, index, imsize=1024):\n",
    "        \"\"\" \n",
    "        This implementation of cutmix author:  https://www.kaggle.com/nvnnghia \n",
    "        Refactoring and adaptation: https://www.kaggle.com/shonenkov\n",
    "        \"\"\"\n",
    "        w, h = imsize, imsize\n",
    "        s = imsize // 2\n",
    "    \n",
    "        xc, yc = [int(random.uniform(imsize * 0.25, imsize * 0.75)) for _ in range(2)]  # center x, y\n",
    "        indexes = [index] + [random.randint(0, self.image_ids.shape[0] - 1) for _ in range(3)]\n",
    "\n",
    "        result_image = np.full((imsize, imsize, 3), 1, dtype=np.float32)\n",
    "        result_boxes = []\n",
    "\n",
    "        for i, index in enumerate(indexes):\n",
    "            image, boxes = self.load_image_and_boxes(index)\n",
    "            if i == 0:\n",
    "                x1a, y1a, x2a, y2a = max(xc - w, 0), max(yc - h, 0), xc, yc  # xmin, ymin, xmax, ymax (large image)\n",
    "                x1b, y1b, x2b, y2b = w - (x2a - x1a), h - (y2a - y1a), w, h  # xmin, ymin, xmax, ymax (small image)\n",
    "            elif i == 1:  # top right\n",
    "                x1a, y1a, x2a, y2a = xc, max(yc - h, 0), min(xc + w, s * 2), yc\n",
    "                x1b, y1b, x2b, y2b = 0, h - (y2a - y1a), min(w, x2a - x1a), h\n",
    "            elif i == 2:  # bottom left\n",
    "                x1a, y1a, x2a, y2a = max(xc - w, 0), yc, xc, min(s * 2, yc + h)\n",
    "                x1b, y1b, x2b, y2b = w - (x2a - x1a), 0, max(xc, w), min(y2a - y1a, h)\n",
    "            elif i == 3:  # bottom right\n",
    "                x1a, y1a, x2a, y2a = xc, yc, min(xc + w, s * 2), min(s * 2, yc + h)\n",
    "                x1b, y1b, x2b, y2b = 0, 0, min(w, x2a - x1a), min(y2a - y1a, h)\n",
    "            result_image[y1a:y2a, x1a:x2a] = image[y1b:y2b, x1b:x2b]\n",
    "            padw = x1a - x1b\n",
    "            padh = y1a - y1b\n",
    "\n",
    "            boxes[:, 0] += padw\n",
    "            boxes[:, 1] += padh\n",
    "            boxes[:, 2] += padw\n",
    "            boxes[:, 3] += padh\n",
    "\n",
    "            result_boxes.append(boxes)\n",
    "\n",
    "        result_boxes = np.concatenate(result_boxes, 0)\n",
    "        np.clip(result_boxes[:, 0:], 0, 2 * s, out=result_boxes[:, 0:])\n",
    "        result_boxes = result_boxes.astype(np.int32)\n",
    "        result_boxes = result_boxes[np.where((result_boxes[:,2]-result_boxes[:,0])*(result_boxes[:,3]-result_boxes[:,1]) > 0)]\n",
    "        return result_image, result_boxes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "fold_number = 3\n",
    "\n",
    "train_dataset = DatasetRetriever(\n",
    "    image_ids=df_folds[df_folds['fold'] != fold_number].index.values,\n",
    "    marking=marking,\n",
    "    transforms=get_train_transforms(),\n",
    "    test=False,\n",
    ")\n",
    "\n",
    "validation_dataset = DatasetRetriever(\n",
    "    image_ids=df_folds[df_folds['fold'] == fold_number].index.values,\n",
    "    marking=marking,\n",
    "    transforms=get_valid_transforms(),\n",
    "    test=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "image, target, image_id = train_dataset[1]\n",
    "boxes = target['boxes'].cpu().numpy().astype(np.int32)\n",
    "\n",
    "numpy_image = image.permute(1,2,0).cpu().numpy()\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(16, 8))\n",
    "\n",
    "for box in boxes:\n",
    "    cv2.rectangle(numpy_image, (box[1], box[0]), (box[3],  box[2]), (0, 1, 0), 2)\n",
    "    \n",
    "ax.set_axis_off()\n",
    "ax.imshow(numpy_image);"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "## Fitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AverageMeter(object):\n",
    "    \"\"\"Computes and stores the average and current value\"\"\"\n",
    "    def __init__(self):\n",
    "        self.reset()\n",
    "\n",
    "    def reset(self):\n",
    "        self.val = 0\n",
    "        self.avg = 0\n",
    "        self.sum = 0\n",
    "        self.count = 0\n",
    "\n",
    "    def update(self, val, n=1):\n",
    "        self.val = val\n",
    "        self.sum += val * n\n",
    "        self.count += n\n",
    "        self.avg = self.sum / self.count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "class Fitter:\n",
    "    \n",
    "    def __init__(self, model, device, config):\n",
    "        self.config = config\n",
    "        self.epoch = 0\n",
    "\n",
    "        self.base_dir = f'./{config.folder}'\n",
    "        if not os.path.exists(self.base_dir):\n",
    "            os.makedirs(self.base_dir)\n",
    "        \n",
    "        self.log_path = f'{self.base_dir}/log.txt'\n",
    "        self.best_summary_loss = 10**5\n",
    "\n",
    "        self.model = model\n",
    "        self.device = device\n",
    "\n",
    "        param_optimizer = list(self.model.named_parameters())\n",
    "        no_decay = ['bias', 'LayerNorm.bias', 'LayerNorm.weight']\n",
    "        optimizer_grouped_parameters = [\n",
    "            {'params': [p for n, p in param_optimizer if not any(nd in n for nd in no_decay)], 'weight_decay': 0.001},\n",
    "            {'params': [p for n, p in param_optimizer if any(nd in n for nd in no_decay)], 'weight_decay': 0.0}\n",
    "        ] \n",
    "\n",
    "        self.optimizer = torch.optim.AdamW(self.model.parameters(), lr=config.lr)\n",
    "        self.scheduler = config.SchedulerClass(self.optimizer, **config.scheduler_params)\n",
    "        self.log(f'Fitter prepared. Device is {self.device}')\n",
    "\n",
    "    def fit(self, train_loader, validation_loader):\n",
    "        for e in range(self.config.n_epochs):\n",
    "            if self.config.verbose:\n",
    "                lr = self.optimizer.param_groups[0]['lr']\n",
    "                timestamp = datetime.utcnow().isoformat()\n",
    "                self.log(f'\\n{timestamp}\\nLR: {lr}')\n",
    "\n",
    "            t = time.time()\n",
    "            summary_loss = self.train_one_epoch(train_loader)\n",
    "\n",
    "            self.log(f'[RESULT]: Train. Epoch: {self.epoch}, summary_loss: {summary_loss.avg:.5f}, time: {(time.time() - t):.5f}')\n",
    "            self.save(f'{self.base_dir}/last-checkpoint.bin')\n",
    "\n",
    "            t = time.time()\n",
    "            summary_loss = self.validation(validation_loader)\n",
    "\n",
    "            self.log(f'[RESULT]: Val. Epoch: {self.epoch}, summary_loss: {summary_loss.avg:.5f}, time: {(time.time() - t):.5f}')\n",
    "            if summary_loss.avg < self.best_summary_loss:\n",
    "                self.best_summary_loss = summary_loss.avg\n",
    "                self.model.eval()\n",
    "                self.save(f'{self.base_dir}/best-checkpoint-{str(self.epoch).zfill(3)}epoch.bin')\n",
    "                for path in sorted(glob(f'{self.base_dir}/best-checkpoint-*epoch.bin'))[:-3]:\n",
    "                    os.remove(path)\n",
    "\n",
    "            if self.config.validation_scheduler:\n",
    "                self.scheduler.step(metrics=summary_loss.avg)\n",
    "\n",
    "            self.epoch += 1\n",
    "\n",
    "    def validation(self, val_loader):\n",
    "        self.model.eval()\n",
    "        summary_loss = AverageMeter()\n",
    "        t = time.time()\n",
    "        for step, (images, targets, image_ids) in enumerate(val_loader):\n",
    "            if self.config.verbose:\n",
    "                if step % self.config.verbose_step == 0:\n",
    "                    print(\n",
    "                        f'Val Step {step}/{len(val_loader)}, ' + \\\n",
    "                        f'summary_loss: {summary_loss.avg:.5f}, ' + \\\n",
    "                        f'time: {(time.time() - t):.5f}', end='\\r'\n",
    "                    )\n",
    "            with torch.no_grad():\n",
    "                images = torch.stack(images)\n",
    "                batch_size = images.shape[0]\n",
    "                images = images.to(self.device).float()\n",
    "                boxes = [target['boxes'].to(self.device).float() for target in targets]\n",
    "                labels = [target['labels'].to(self.device).float() for target in targets]\n",
    "\n",
    "                loss, _, _ = self.model(images, boxes, labels)\n",
    "                summary_loss.update(loss.detach().item(), batch_size)\n",
    "\n",
    "        return summary_loss\n",
    "\n",
    "    def train_one_epoch(self, train_loader):\n",
    "        self.model.train()\n",
    "        summary_loss = AverageMeter()\n",
    "        t = time.time()\n",
    "        for step, (images, targets, image_ids) in enumerate(train_loader):\n",
    "            if self.config.verbose:\n",
    "                if step % self.config.verbose_step == 0:\n",
    "                    print(\n",
    "                        f'Train Step {step}/{len(train_loader)}, ' + \\\n",
    "                        f'summary_loss: {summary_loss.avg:.5f}, ' + \\\n",
    "                        f'time: {(time.time() - t):.5f}', end='\\r'\n",
    "                    )\n",
    "            \n",
    "            images = torch.stack(images)\n",
    "            images = images.to(self.device).float()\n",
    "            batch_size = images.shape[0]\n",
    "            boxes = [target['boxes'].to(self.device).float() for target in targets]\n",
    "            labels = [target['labels'].to(self.device).float() for target in targets]\n",
    "\n",
    "            self.optimizer.zero_grad()\n",
    "            \n",
    "            loss, _, _ = self.model(images, boxes, labels)\n",
    "            \n",
    "            loss.backward()\n",
    "\n",
    "            summary_loss.update(loss.detach().item(), batch_size)\n",
    "\n",
    "            self.optimizer.step()\n",
    "\n",
    "            if self.config.step_scheduler:\n",
    "                self.scheduler.step()\n",
    "\n",
    "        return summary_loss\n",
    "    \n",
    "    def save(self, path):\n",
    "        self.model.eval()\n",
    "        torch.save({\n",
    "            'model_state_dict': self.model.model.state_dict(),\n",
    "            'optimizer_state_dict': self.optimizer.state_dict(),\n",
    "            'scheduler_state_dict': self.scheduler.state_dict(),\n",
    "            'best_summary_loss': self.best_summary_loss,\n",
    "            'epoch': self.epoch,\n",
    "        }, path)\n",
    "\n",
    "    def load(self, path):\n",
    "        checkpoint = torch.load(path)\n",
    "        self.model.model.load_state_dict(checkpoint['model_state_dict'])\n",
    "        self.optimizer.load_state_dict(checkpoint['optimizer_state_dict'])\n",
    "        self.scheduler.load_state_dict(checkpoint['scheduler_state_dict'])\n",
    "        self.best_summary_loss = checkpoint['best_summary_loss']\n",
    "        self.epoch = checkpoint['epoch'] + 1\n",
    "        \n",
    "    def log(self, message):\n",
    "        if self.config.verbose:\n",
    "            print(message)\n",
    "        with open(self.log_path, 'a+') as logger:\n",
    "            logger.write(f'{message}\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TrainGlobalConfig:\n",
    "    num_workers = 2\n",
    "    batch_size = 4 \n",
    "    n_epochs = 30\n",
    "    lr = 0.0002\n",
    "\n",
    "    folder = 'fold3-effdet5-cutmix-augmix'\n",
    "\n",
    "    verbose = True\n",
    "    verbose_step = 1\n",
    "\n",
    "    step_scheduler = False  # do scheduler.step after optimizer.step\n",
    "    validation_scheduler = True  # do scheduler.step after validation stage loss\n",
    "    \n",
    "    SchedulerClass = torch.optim.lr_scheduler.ReduceLROnPlateau\n",
    "    scheduler_params = dict(\n",
    "        mode='min',\n",
    "        factor=0.5,\n",
    "        patience=1,\n",
    "        verbose=False, \n",
    "        threshold=0.0001,\n",
    "        threshold_mode='abs',\n",
    "        cooldown=0, \n",
    "        min_lr=1e-8,\n",
    "        eps=1e-08\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def collate_fn(batch):\n",
    "    return tuple(zip(*batch))\n",
    "\n",
    "def run_training():\n",
    "    device = torch.device('cuda:0')\n",
    "    net.to(device)\n",
    "\n",
    "    train_loader = torch.utils.data.DataLoader(\n",
    "        train_dataset,\n",
    "        batch_size=TrainGlobalConfig.batch_size,\n",
    "        sampler=RandomSampler(train_dataset),\n",
    "        pin_memory=False,\n",
    "        drop_last=True,\n",
    "        num_workers=TrainGlobalConfig.num_workers,\n",
    "        collate_fn=collate_fn,\n",
    "    )\n",
    "    val_loader = torch.utils.data.DataLoader(\n",
    "        validation_dataset, \n",
    "        batch_size=TrainGlobalConfig.batch_size,\n",
    "        num_workers=TrainGlobalConfig.num_workers,\n",
    "        shuffle=False,\n",
    "        sampler=SequentialSampler(validation_dataset),\n",
    "        pin_memory=False,\n",
    "        collate_fn=collate_fn,\n",
    "    )\n",
    "\n",
    "    fitter = Fitter(model=net, device=device, config=TrainGlobalConfig)\n",
    "    fitter.fit(train_loader, val_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from effdet import get_efficientdet_config, EfficientDet, DetBenchTrain\n",
    "from effdet.efficientdet import HeadNet\n",
    "\n",
    "def get_net():\n",
    "    config = get_efficientdet_config('tf_efficientdet_d5')\n",
    "    net = EfficientDet(config, pretrained_backbone=False)\n",
    "    checkpoint = torch.load('../input/efficientdet/efficientdet_d5-ef44aea8.pth')\n",
    "    net.load_state_dict(checkpoint)\n",
    "    config.num_classes = 1\n",
    "    config.image_size = 512\n",
    "    net.class_net = HeadNet(config, num_outputs=config.num_classes, norm_kwargs=dict(eps=.001, momentum=.01))\n",
    "    return DetBenchTrain(net, config)\n",
    "\n",
    "net = get_net()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitter prepared. Device is cuda:0\n",
      "\n",
      "2020-06-04T03:38:00.021688\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 0, summary_loss: 1.85886, time: 616.76439\n",
      "[RESULT]: Val. Epoch: 0, summary_loss: 0.48392, time: 44.64612\n",
      "\n",
      "2020-06-04T03:49:02.717810\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 1, summary_loss: 0.49735, time: 610.77604\n",
      "[RESULT]: Val. Epoch: 1, summary_loss: 0.42590, time: 42.17833\n",
      "\n",
      "2020-06-04T03:59:57.146460\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 2, summary_loss: 0.46899, time: 602.28822\n",
      "[RESULT]: Val. Epoch: 2, summary_loss: 0.41028, time: 43.02728\n",
      "\n",
      "2020-06-04T04:10:44.061537\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 3, summary_loss: 0.45660, time: 608.38922\n",
      "[RESULT]: Val. Epoch: 3, summary_loss: 0.39394, time: 43.09595\n",
      "\n",
      "2020-06-04T04:21:37.033542\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 4, summary_loss: 0.45179, time: 607.86300\n",
      "[RESULT]: Val. Epoch: 4, summary_loss: 0.40718, time: 43.34863\n",
      "\n",
      "2020-06-04T04:32:29.114075\n",
      "LR: 0.0002\n",
      "[RESULT]: Train. Epoch: 5, summary_loss: 0.44316, time: 606.20245\n",
      "[RESULT]: Val. Epoch: 5, summary_loss: 0.40469, time: 43.36998\n",
      "\n",
      "2020-06-04T04:43:19.650019\n",
      "LR: 0.0001\n",
      "[RESULT]: Train. Epoch: 6, summary_loss: 0.42957, time: 608.30958\n",
      "[RESULT]: Val. Epoch: 6, summary_loss: 0.37783, time: 43.99373\n",
      "\n",
      "2020-06-04T04:54:13.595853\n",
      "LR: 0.0001\n",
      "[RESULT]: Train. Epoch: 7, summary_loss: 0.42386, time: 611.25681\n",
      "[RESULT]: Val. Epoch: 7, summary_loss: 0.37626, time: 44.33623\n",
      "\n",
      "2020-06-04T05:05:10.939796\n",
      "LR: 0.0001\n",
      "[RESULT]: Train. Epoch: 8, summary_loss: 0.42185, time: 613.91071\n",
      "[RESULT]: Val. Epoch: 8, summary_loss: 0.37693, time: 43.56476\n",
      "\n",
      "2020-06-04T05:16:09.258319\n",
      "LR: 0.0001\n",
      "[RESULT]: Train. Epoch: 9, summary_loss: 0.41631, time: 606.11121\n",
      "[RESULT]: Val. Epoch: 9, summary_loss: 0.37732, time: 42.31080\n",
      "\n",
      "2020-06-04T05:26:58.551787\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 10, summary_loss: 0.40950, time: 612.91745\n",
      "[RESULT]: Val. Epoch: 10, summary_loss: 0.37084, time: 42.60785\n",
      "\n",
      "2020-06-04T05:37:55.642154\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 11, summary_loss: 0.40575, time: 613.69852\n",
      "[RESULT]: Val. Epoch: 11, summary_loss: 0.36756, time: 42.94553\n",
      "\n",
      "2020-06-04T05:48:53.769683\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 12, summary_loss: 0.40745, time: 612.29046\n",
      "[RESULT]: Val. Epoch: 12, summary_loss: 0.37077, time: 42.42423\n",
      "\n",
      "2020-06-04T05:59:49.382957\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 13, summary_loss: 0.40143, time: 615.79575\n",
      "[RESULT]: Val. Epoch: 13, summary_loss: 0.36671, time: 42.61115\n",
      "\n",
      "2020-06-04T06:10:49.347056\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 14, summary_loss: 0.40466, time: 694.85274\n",
      "[RESULT]: Val. Epoch: 14, summary_loss: 0.36903, time: 46.22666\n",
      "\n",
      "2020-06-04T06:23:11.266805\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 15, summary_loss: 0.40117, time: 621.53176\n",
      "[RESULT]: Val. Epoch: 15, summary_loss: 0.36508, time: 43.44812\n",
      "\n",
      "2020-06-04T06:34:17.678057\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 16, summary_loss: 0.40025, time: 614.50257\n",
      "[RESULT]: Val. Epoch: 16, summary_loss: 0.37086, time: 44.46853\n",
      "\n",
      "2020-06-04T06:45:17.484767\n",
      "LR: 5e-05\n",
      "[RESULT]: Train. Epoch: 17, summary_loss: 0.39840, time: 621.40002\n",
      "[RESULT]: Val. Epoch: 17, summary_loss: 0.36656, time: 43.45503\n",
      "\n",
      "2020-06-04T06:56:23.268102\n",
      "LR: 2.5e-05\n",
      "[RESULT]: Train. Epoch: 18, summary_loss: 0.39272, time: 615.81597\n",
      "[RESULT]: Val. Epoch: 18, summary_loss: 0.36621, time: 43.47928\n",
      "\n",
      "2020-06-04T07:07:23.387375\n",
      "LR: 2.5e-05\n",
      "[RESULT]: Train. Epoch: 19, summary_loss: 0.39338, time: 608.62515\n",
      "[RESULT]: Val. Epoch: 19, summary_loss: 0.36393, time: 43.04374\n",
      "\n",
      "2020-06-04T07:18:16.730677\n",
      "LR: 2.5e-05\n",
      "[RESULT]: Train. Epoch: 20, summary_loss: 0.39090, time: 606.18300\n",
      "[RESULT]: Val. Epoch: 20, summary_loss: 0.36550, time: 42.99828\n",
      "\n",
      "2020-06-04T07:29:06.796092\n",
      "LR: 2.5e-05\n",
      "[RESULT]: Train. Epoch: 21, summary_loss: 0.39020, time: 621.45651\n",
      "[RESULT]: Val. Epoch: 21, summary_loss: 0.36739, time: 51.43745\n",
      "\n",
      "2020-06-04T07:40:20.607824\n",
      "LR: 1.25e-05\n",
      "[RESULT]: Train. Epoch: 22, summary_loss: 0.38824, time: 615.33275\n",
      "[RESULT]: Val. Epoch: 22, summary_loss: 0.36248, time: 43.18657\n",
      "\n",
      "2020-06-04T07:51:20.584696\n",
      "LR: 1.25e-05\n",
      "[RESULT]: Train. Epoch: 23, summary_loss: 0.38880, time: 623.91042\n",
      "[RESULT]: Val. Epoch: 23, summary_loss: 0.36510, time: 43.32095\n",
      "\n",
      "2020-06-04T08:02:28.650260\n",
      "LR: 1.25e-05\n",
      "[RESULT]: Train. Epoch: 24, summary_loss: 0.38903, time: 606.94592\n",
      "[RESULT]: Val. Epoch: 24, summary_loss: 0.36325, time: 43.04321\n",
      "\n",
      "2020-06-04T08:13:19.472314\n",
      "LR: 6.25e-06\n",
      "[RESULT]: Train. Epoch: 25, summary_loss: 0.38714, time: 608.88932\n",
      "[RESULT]: Val. Epoch: 25, summary_loss: 0.36348, time: 43.21746\n",
      "\n",
      "2020-06-04T08:24:12.512562\n",
      "LR: 6.25e-06\n",
      "[RESULT]: Train. Epoch: 26, summary_loss: 0.38716, time: 605.63796\n",
      "[RESULT]: Val. Epoch: 26, summary_loss: 0.36467, time: 42.41007\n",
      "\n",
      "2020-06-04T08:35:01.586542\n",
      "LR: 3.125e-06\n",
      "[RESULT]: Train. Epoch: 27, summary_loss: 0.38867, time: 603.12121\n",
      "[RESULT]: Val. Epoch: 27, summary_loss: 0.36382, time: 42.40288\n",
      "\n",
      "2020-06-04T08:45:47.966030\n",
      "LR: 3.125e-06\n",
      "[RESULT]: Train. Epoch: 28, summary_loss: 0.38393, time: 606.01166\n",
      "[RESULT]: Val. Epoch: 28, summary_loss: 0.36309, time: 43.69342\n",
      "\n",
      "2020-06-04T08:56:38.514688\n",
      "LR: 1.5625e-06\n",
      "[RESULT]: Train. Epoch: 29, summary_loss: 0.38570, time: 621.39448\n",
      "[RESULT]: Val. Epoch: 29, summary_loss: 0.36315, time: 43.25415\n"
     ]
    }
   ],
   "source": [
    "run_training()"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "metadata": {},
   "source": [
    "### Thank you for reading my kernel!\n",
    "\n",
    "So, I have prepared good training SOTA-model baseline for you, my friends! I have used n_epochs = 40 and have got best checkpoint single model that gives 0.7176 LB. You can see [here](https://www.kaggle.com/shonenkov/inference-efficientdet) inference kernel.\n",
    "\n",
    "Just recently I have started publishing my works, if you like this format of notebooks I would like continue to make kernels."
   ]
  }
 ],
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